Semiparametric regression methods for temporal processes subject to multiple sources of censoring [0.03%]
多重截尾下时间过程的半参数回归方法研究
Tianyu Zhan,Douglas E Schaubel
Tianyu Zhan
Process regression methodology is underdeveloped relative to the frequency with which pertinent data arise. In this article, the response is a binary indicator process representing the joint event of being alive and remaining in a specific ...
Alexander W Levis,Rajarshi Mukherjee,Rui Wang et al.
Alexander W Levis et al.
Large observational databases are often subject to missing data. As such, methods for causal inference must simultaneously handle confounding and missingness; surprisingly little work has been done at this intersection. Motivated by this, w...
Debiased lasso after sample splitting for estimation and inference in high-dimensional generalized linear models [0.03%]
高维广义线性模型中用于估计和推断的拆分样本去偏lasso方法
Omar Vazquez,Bin Nan
Omar Vazquez
We consider random sample splitting for estimation and inference in high dimensional generalized linear models, where we first apply the lasso to select a submodel using one subsample and then apply the debiased lasso to fit the selected mo...
Variable selection in modelling clustered data via within-cluster resampling [0.03%]
通过集群内重采样在建模聚类数据中的变量选择
Shangyuan Ye,Tingting Yu,Daniel A Caroff et al.
Shangyuan Ye et al.
In many biomedical applications, there is a need to build risk-adjustment models based on clustered data. However, methods for variable selection that are applicable to clustered discrete data settings with a large number of candidate varia...
Robust Estimation of Loss-Based Measures of Model Performance under Covariate Shift [0.03%]
协变量变化下的损失型模型评估的稳健估计方法研究
Samantha Morrison,Constantine Gatsonis,Issa J Dahabreh et al.
Samantha Morrison et al.
We present methods for estimating loss-based measures of the performance of a prediction model in a target population that differs from the source population in which the model was developed, in settings where outcome and covariate data are...
Optimal multiwave validation of secondary use data with outcome and exposure misclassification [0.03%]
具有结局和暴露分类错误的二次使用数据的多波验证的最佳方法
Sarah C Lotspeich,Gustavo G C Amorim,Pamela A Shaw et al.
Sarah C Lotspeich et al.
Observational databases provide unprecedented opportunities for secondary use in biomedical research. However, these data can be error-prone and must be validated before use. It is usually unrealistic to validate the whole database because ...
Peter A Gao,Jon Wakefield
Peter A Gao
In countries where population census data are limited, generating accurate subnational estimates of health and demographic indicators is challenging. Existing model-based geostatistical methods leverage covariate information and spatial smo...
High-dimensional variable selection accounting for heterogeneity in regression coefficients across multiple data sources [0.03%]
利用多个数据源间的回归系数异质性进行高维变量选择
Tingting Yu,Shangyuan Ye,Rui Wang
Tingting Yu
When analyzing data combined from multiple sources (e.g., hospitals, studies), the heterogeneity across different sources must be accounted for. In this paper, we consider high-dimensional linear regression models for integrative data analy...
Oscillating neural circuits: Phase, amplitude, and the complex normal distribution [0.03%]
振荡神经回路：相位，幅度和复数正态分布
Konrad N Urban,Heejong Bong,Josue Orellana et al.
Konrad N Urban et al.
Multiple oscillating time series are typically analyzed in the frequency domain, where coherence is usually said to represent the magnitude of the correlation between two signals at a particular frequency. The correlation being referenced i...
Ana F Best,David B Wolfson
Ana F Best
The determination of risk factors for disease incidence has been the subject of much epidemiologic research. With this goal a common study design entails the follow-up of an initially disease-free cohort, keeping track of the dates of disea...